atomistic simulations 1binary alloys 1configurational entropy 1phase diagrams 1vibrational entropy 1
From the 1 of 3 linked papers with an AI index.
3 papers
cond-mat.mtrl-sci2026
Data-Efficient Training of Linear ACE Potentials through Leverage-Guided Subset Selection of ASSYST Structure Pools
Aynour Khosravi, Marvin Poul, Jörg Neugebauer +1
The construction of machine-learned interatomic potentials (MLIPs) is often limited by the cost of generating large density-functional-theory (DFT) training datasets. For systemati…
cond-mat.mtrl-sci2026
Computing binary alloy phase diagrams with explicit configurational and vibrational entropy
Sarath Menon, Marvin Poul, Tilmann Hickel +2
The paper introduces a combined non‑equilibrium thermodynamic integration, Monte Carlo identity exchange, and molecular dynamics approach to compute binary alloy phase diagrams tha…
cond-mat.mtrl-sci2026
Triple Junctions as Dislocation-Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation
Tobias Brink, Saba Saood, Peter Schweizer +2
Grain boundary networks and their evolution are strongly influenced by triple junctions. The defect nature of these line defects significantly affects the properties of the network…